The present invention, in some embodiments thereof, relates to medical anatomical images and, more specifically, but not exclusively, to a convolutional neural network for segmentation of at least one anatomical feature in medical anatomical images.
Manual visual assessment (e.g., by a radiologist) of medical anatomical images (e.g., CT, MRI, ultrasound, each of different parts of the body, for example, chest) for identification of abnormal anatomical features is a challenging and time consuming task due to the large amount of information that needs to be processed. For example, for a 3D CT and/or MRI image, a radiologist examines dozens or hundreds of 2D slices.